Samisa Abeysinghe, Ajantha S. Atukorale
This paper is a review paper on research done on imperfect information games. It is focused on the card game poker, on which much research has been done over the years. The paper reviews the solutions researchers have proposed for various problems of the game of poker. The main challenges in this imperfect information game are searching, learning, opponent modeling and deception. Machine learning, pattern recognition, adaptive evolutionary techniques, statistics and simulation are some of the technologies explored in this highly complex problem domain. This paper introduces the rationale for research on imperfect information games, describes the techniques used in solving the problems, review some successful programs built to solve such problems and finally discuss research opportunities in this area.